A comparative study of the ensemble and base classifiers performance in Malay text categorization

Alshalabi, Hamood Ali and Sabrina Tiun, and Nazlia Omar, (2017) A comparative study of the ensemble and base classifiers performance in Malay text categorization. Asia-Pacific Journal of Information Technology and Multimedia, 6 (2). pp. 53-64. ISSN 2289-2192


Official URL: http://ejournals.ukm.my/apjitm/issue/view/1050


Automatic text categorization (ATC) has attracted the attention of the research community over the last decade as it frees organizations from the need of manually organized documents. The ensemble techniques, which combine the results of a number of individually trained base classifiers, always improve classification performance better than base classifiers. This paper intends to compare the effectiveness of ensemble with that of base classifiers for Malay text classification. Two feature selection methods (the Gini Index (GI) and Chi-square) with the ensemble methods are applied to examine Malay text classification, with the intention to efficiently integrate base classifiers algorithms into a more accurate classification procedure. Two types of ensemble methods, namely the voting combination and meta-classifier combination, are evaluated. A wide range of comparative experiments are conducted to assess classified Malay dataset. The applied experiments reveal that meta-classifier ensemble framework performed better than the best individual classifiers on the tested datasets.

Item Type:Article
Keywords:Feature selection; Individual classifiers; Ensemble classifiers; Malay text classification
Journal:Asia - Pasific Journal of Information Technology and Multimedia (Formerly Jurnal Teknologi Maklumat dan Multimedia)
ID Code:11854
Deposited By: ms aida -
Deposited On:04 Jul 2018 01:18
Last Modified:10 Jul 2018 00:05

Repository Staff Only: item control page